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A new analytical method to aid in the understanding of the organic carbon (OC) phase of particulate matter (PM) from advanced compression ignition (ACI) operating modes, is presented. The presence of NO2 and unburned fuel aromatics in ACI emissions, and the low exhaust temperatures that result from this low temperature combustion strategy, provide the right conditions for the formation of carboxylic acids and nitroaromatic compounds. These polar compounds contribute to OC in the PM and are not typically measured using nonpolar solvent extraction methods such as the soluble organic fraction (SOF) method. The new extraction and detection method employs capillary electrophoresis with electrospray ionization mass spectrometry (CE-ESI MS) and was specifically developed to determine polar organic compounds in the ACI PM emissions. The new method identified both nitrophenols and aromatic carboxylic acids in the ACI PM.

Reactivity Controlled Compression Ignition (RCCI) is an engine combustion strategy that produces low NO and PM emissions with high thermal efficiency. Previous RCCI research has been investigated in single-cylinder heavy-duty engines. The current study investigates RCCI operation in a light-duty multi-cylinder engine at 3 operating points. These operating points were chosen to cover a range of conditions seen in the US EPA light-duty FTP test. The operating points were chosen by the Ad Hoc working group to simulate operation in the FTP test. The fueling strategy for the engine experiments consisted of in-cylinder fuel blending using port fuel-injection (PFI) of gasoline and early-cycle, direct-injection (DI) of diesel fuel. At these 3 points, the stock engine configuration is compared to operation with both the original equipment manufacturer (OEM) and custom-machined pistons designed for RCCI operation.

In-cylinder blending of gasoline and diesel to achieve Reactivity Controlled Compression Ignition (RCCI) has been shown to reduce NOX and particulate matter (PM) emissions while maintaining or improving brake thermal efficiency as compared to conventional diesel combustion (CDC). The RCCI concept has an advantage over many advanced combustion strategies in that the fuel reactivity can be tailored to the engine speed and load allowing stable low-temperature combustion to be extended over more of the light-duty drive cycle load range. Varying the premixed gasoline fraction changes the fuel reactivity stratification in the cylinder providing further control of combustion phasing and pressure rise rate than the use of EGR alone. This added control over the combustion process has been shown to allow rapid engine operating point exploration without direct modeling guidance.

Rapid vehicle powertrain development has become a technological breakthrough for the design and implementation of vehicles that meet and exceed the fuel efficiency, cost, and performance targets expected by today’s consumer. Recently, advances in large scale additive manufacturing have provided the means to bridge hardware-in-the-loop with preproduction mule chassis testing. This paper details a case study from Oak Ridge National Laboratory bridging the powertrain-in-the-loop development process with vehicle systems implementation using big area additive manufacturing (BAAM). For this case study, the use of a component-in-the-loop laboratory with math-based models is detailed for the design of a battery electric powertrain to be implemented in a printed prototype mule. The ability for BAAM to accelerate the mule development process via the concept of computer-aided design to part is explored.

The US Department of Energy’s Co-Optimization of Engine and Fuels Initiative (Co-Optima) investigated how unique properties of bio-blendstocks considered within Co-Optima help address emissions challenges with mixing controlled compression ignition (i.e., conventional diesel combustion) and enable advanced compression ignition modes suitable for implementation in a diesel engine. Additionally, the potential synergies of these Co-Optima technologies in hybrid vehicle applications in the medium- and heavy-duty sector was also investigated. In this work, vehicles system were simulated using the Autonomie software tool for quantifying the benefits of Co-Optima engine technologies for medium-duty trucks. A Class 6 delivery truck with a 6.7 L diesel engine was used for simulations over representative real-world and certification drive cycles with four different powertrains to investigate fuel economy, criteria emissions, and performance.